Table of Contents Author Guidelines Submit a Manuscript
Journal of Spectroscopy
Volume 2016, Article ID 8515672, 8 pages
Research Article

Backward Spectral Characterization of Liquid Crystal Display Based on Forward Spectral Characterization

1University of Shanghai for Science and Technology, Shanghai 200093, China
2College of Engineering, Qufu Normal University, Rizhao, Shandong 276826, China
3Navy Marine Environment Office, Beijing 100081, China
4Henan University of Engineering, Zhengzhou, Henan 451191, China

Received 20 December 2015; Accepted 15 March 2016

Academic Editor: Michele Fedel

Copyright © 2016 Jian-qing Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A backward spectral characterization for Liquid Crystal Display by the use of rule for the maximum peak of spectral radiation curves changing with the digital input values is proposed; this new model is developed based on forward spectral characterization. It deals with estimation of RGB used as input to the digital display from known spectral radiation curves. We first investigate the rule for the peak of spectral radiation curves changing with the digital input values of primaries; then the initial digital input RGB are calculated based on that rule using the known spectral radiation curves . Third, RGB are inputted into forward spectral characterization model and the corresponding spectral radiation curves are predicted. Last, RGB are modified according to the difference between predicted and known , until this difference satisfied the prediction accuracy of the inverse characterization model. The inverse model has the advantage of using the same model for both forward and inverse color space transformation. This improves the accuracy of the color space transformation and reduces the source of errors. Results for 3 devices are shown and discussed; the accuracy of this model is considered sufficient for many applications.